Technical analysis profitability when exchange rates are pegged: A note

Abstract

This note extends earlier results which concluded that generally technical analysis trading rules were profitable when applied to several US dollar exchange rates. These results were linked to the presence of long swings in the dollar series, and here, it is tested whether they still hold in a different setting, with a quasi-fixed exchange rate system. Applying non-parametric and parametric tests to the main European currencies does not allow to confirm, in this case, the profitability of these rules. These results strengthen the likelihood of the hypothesis of a causal link from the exchange rate DGP to the profitability of technical analysis trading rules, as already highlighted in several articles.     

Technical analysis as the representation of typical cognitive biases

The present research provides a justification for the popularity of the technical analysis. It finds that financial analysts firmly discriminate between two types of technical signals—those based on typical cognitive biases and “empty” signals that sound like a technical analysis but are without any connotation with psychological inclinations.At the same time that they treat them differently, different analysts rate these items very similarly. These results suggest that the popularity of technical analysis is associated with its relation to the typical cognitive biases of humans.     

Consumer confidence indices and stock markets' meltdowns

Consumer confidence indices (CCIs) are a closely monitored barometer of countries' economic health and an informative forecasting tool. Using European and US data, we provide a case study of the two recent stock market meltdowns (the post-dotcom bubble correction of 2000–2002 and the 2007–2009 decline at the beginning of the financial crisis) to contribute to the discussion on their appropriateness as proxies for stock markets' investor sentiment. Investor sentiment should positively covary with stock market movements [DeLong, Shleifer, Summers, and Waldmann. 1990. “Noise Trader Risk in Financial Markets.” Journal of Political Economy 98 (4): 703–738]; however, we find that the CCI–stock market relationship is not universally positive. We also do not find support for the information effect documented in the previous literature, but identify a more subtle relationship between consumer expectations about future household finances and stock market fluctuations.     

信贷资产交易的国际经验及启示

贷款转让平台的上线,标志着银行信贷资产从此有了全国性统一规范的公共交易平台。文章借鉴信贷资产交易的国际经验,结合起步中的我国信贷转让市场所面临的不足,提出通过推动信贷转让流程标准化、开发定价服务信息平台、引入并培育市场投资者以及促进评级、法律等中介机构发挥作用等途径,不断完善贷款转让市场建设,并建议有关部门加强政策扶持与引导,渐进完善市场后续的监管制度。     

Big data tools for Islamic financial analysis

Behavioural science states that emotions, principles and the manner of thinking can affect the behaviour of individuals and even investors in their decision making on financial markets. In this paper, we have tried to measure the investor sentiment by three means of big data. The first is based on a search query of a list of words related to Islamic context. The second is inferred from the engagement degree on social media. The last measure of sentiment is built, based on the Twitter API classified into positive and negative directions by a machine learning algorithm based on the naive Bayes method. Then, we investigate whether these sensations and emotions have an impact on the market sentiment and the price fluctuations by means of a vector autoregression model and Granger causality analysis. In the final step, we apply the agent‐based simulation by means of the sequential Monte Carlo method with the control of our Twitter measure on Islamic index returns. We show, then, that the three social media sentiment measures present a remarkable impact on the contemporaneous and lagged returns of the different Islamic assets studied. We also give an estimation of the parameters of the latent variables relative to the agent model studied.     

Aggregate insider trading and market returns: The role of transparency

Using a sample of countries that require timely disclosures of insider trades, I investigate the effect of country‐level institutions that promote transparency on the extent to which aggregate insider trades predict market returns. I find that financial information transparency mitigates the predictive content of aggregate insider trades when markets are more likely to deviate from fundamentals (i.e., during market fads), and when there is greater co‐movement in stock prices. In contrast, there is some evidence that governance and investor protection mitigate the association between aggregate insider trades and future earnings surprises. Hence, holding constant the timely disclosures of insider trades, other capital market institutions play complementary roles in mitigating the informational frictions that give rise to the predictive content of aggregate insider trades.     

Profitability of alternative methods of combining the signals from technical trading systems

Past efforts determining the profitability of technical analysis reached varied conclusions. We test the profitability of a composite prediction that uses buy and sell signals from technical indicators as inputs. Both machine learning methods, like neural networks, and statistical methods, like logistic regression, are used to get predictions. Inputs are signals from trend‐following and mean‐reversal technical indicators in addition to the variance of prices. Four representative commodities from agricultural, livestock, financial, and foreign exchange futures markets are selected to determine profitability. Special care is taken to avoid data snooping error. Both neural networks and statistical methods did not show consistent profitability.     

Short-horizon contrarian and momentum strategies in Asian markets: An integrated analysis

In this paper, we test the profitability of short-term contrarian and momentum strategies, which take into account the effects of trading activity, size/value characteristics, and asymmetric investor responses to news regarding stock markets in Japan, Taiwan, Korea, Hong Kong, Malaysia, Thailand, and Singapore during 1990-2000. Except for the Taiwanese and Korean markets, “winner” (“loser”) portfolios experience subsequent reversal (momentum) of stock prices. Among actively traded stocks, significant contrarian profits can be obtained from only “winner” portfolios in Japan, while sizeable momentum profits from “loser portfolios” in both Japan and Hong Kong.     

BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing

This systematic literature review summarizes the extant research in the Behavioral Finance (BeFi) and digital asset spaces to understand better the interactions of behavioral effects on the pricing of assets constructed, enabled, and exchanged in Decentralized Finance (DeFi) markets. We find that asset pricing in these rapidly evolving markets is better explained through BeFi than through traditional finance (TradFi) theory. Investor attention, sentiment, heuristics and biases, and network effects interact to form a highly volatile and dynamic market. We offer a deterministic research framework with propositions for future research. We further provide investors with a theoretically and empirically supported structure to better inform their decisions through an understanding of BeFi applications to DeFi.     

The holiday and Yom Kippur War sentiment effects: the Tel Aviv Stock Exchange (TASE)

Several empirical studies reveal that holidays generally create positive sentiment in the stock market, whereas negative events, such as wars or disasters, are accompanied by negative sentiment. However, what happens if a negative event occurs on a holiday? In such a case, we expect two conflicting sentiment effects, which may cancel one another out or, alternatively, one effect may dominate the other. The stock market in Israel provides a unique laboratory in which to test these two conflicting effects, as Israel faced a horrible war on the Yom Kippur holiday in 1973—a war whose influence is still strongly felt today. Indeed, we find two robust effects: A strong and significant positive holiday sentiment effect; and a negative war sentiment effect, which dominates the positive holiday effect. These results, which show how sentiment effects are created, are general and can easily be applied to other events and other markets when conflicting sentiment effects occur.     

技术性贸易壁垒的理论分析与对策研究

目前,技术性贸易壁垒已成为发达国家实施超贸易保护主义政策的载体,从而使原本维护贸易公平竞争、促进国际贸易发展的措施,成为阻碍国际贸易正常发展的手段。技术性贸易壁垒扭曲了比较利益,损害了多方利益。如何应对技术性贸易,应从根源上寻找对策,关键是提高科技水平,实现在技术上超越技术性贸易壁垒的限制。     

基于股市投资者情绪的非理性投机泡沫模型研究

针对股市非理性投机泡沫研究的不足,通过引入投资者情绪构建基于噪声交易者模型的非理性投机泡沫模型,以此研究噪声交易者的认知偏差,其在投资过程中所带有的情绪及其对风险资产历史基础价值冲击的过度反应对股市投机泡沫的影响。结果表明：市场中带情绪的噪声交易者数量越多,股价中的非理性投机泡沫成分越大,其波动程度也越剧烈。     

Overconfidence in investment decisions: An experimental approach

Abstract

By experimentally inducing risk aversion, overconfidence in an investment setting is investigated, comparing the evaluation of actual investment decisions with alternative choices. After selecting their own investment, subjects confront three alternative investment choices, including the optimal one, and are asked about their willingness to pay and to substitute their own for alternative choices. Overconfidence is defined as the persistent overevaluation of the own investment decision. Results indicate that overconfidence increases (i) with the absolute deviation from optimal choices, (ii) with task complexity involving the number of risky assets, and (iii) decreases with individual perceived uncertainty.     

Influence of endogenous reference points on the selling decisions of retail investors

Using trader-level data, we examine the impact of the stock-specific endogenous reference points, the ‘realized-return’ and the ‘peak-return’ of the prior round on the selling propensity in a subsequent investment round in the same asset. The selling propensity rises significantly near the endogenous reference points. The significance is greater when the holding period is relatively shorter and when the time gap between the consecutive rounds is lower, implying a recency effect. Finally, the impact is more substantial on traders holding fewer stocks. The results imply that traders' prior stock-specific experience plays a significant role in the reference point formation.     

Pairs trading based on statistical variability of the spread process

This research proposes a new non-parametric approach to pairs trading based on renko and kagi constructions which originated from Japanese charting indicators and were introduced to academic studies by Pastukhov. The method exploits statistical information about the variability of the tradable process. The approach does not find a long-run mean of the process and trade towards it like other methods of pairs trading. The only assumption we need is that the statistical properties of the spread process volatility remain reasonably constant. The theoretical profitability of the method has been demonstrated for the Ornstein–Uhlenbeck process. Tests on the daily market data of American and Australian stock exchanges show statistically significant average excess returns ranging from 1.4 to 3.6% per month and annualized Sharpe ratio from 1.5 to 3.4.     

基于DEA-BCC模型的城商行技术效率实证分析（2008-2012）

运用投入导向型的DEA-BCC 模型,对东部沿海10省市36家样本城商行2008-2012年的技术效率进行实证研究。研究表明,近五年来样本城商行总体技术效率保持平稳,并呈较为平坦的“V型”变化趋势,样本城商行的技术效率并没有在规模持续扩张的背景下得到持续有效提升。进一步对技术效率的分解项目进行分析发现,纯技术效率是制约样本城商行总体技术效率提升的主导因素,表明,样本城商行的内部管理能力亟待提升。此外,无论是总技术效率、纯技术效率还是规模效率,都与样本城商行的规模具有显著的相关性,总体而言,大型城商行的技术效率及纯技术效率要优于中小型城商行,但是,中型城商行在规模效率方面略胜一筹,样本城商行存在较为明显的“倒V型”成本曲线。     

技术性贸易壁垒对我国外贸的影响及对策探析

随着经济全球化和贸易自由化进程的加快,WTO成员国已不能通过限制数量和高关税为国内产品提供保护。以技术标准为主要内容的技术贸易措施正成为发达国家保护本国产品的最普遍、最难以对付的贸易壁垒。因此,研究并制定相应的对策,突破技术壁垒,具有一定的现实意义。     

Returns,volatility and investor sentiment: Evidence from European stock markets

In this study, we show that patterns in returns behave as if investors, influenced by their level of optimism, selected stocks according to their volatility. Our goal is to confirm the contribution of behavioral finance while showing that investor sentiment can be profitably used by practitioners. We incorporate volatility in the relationship between investor sentiment and future returns, this is the main originality of our approach. Our methodology consists in comparing returns, volatility and higher-order moments of portfolios managed with investor sentiment against those obtained either with passive (buy and hold) portfolio management or with a minimum variance portfolio. Portfolios managed with investor sentiment have better returns and involve less risk under certain conditions.     

Behavioural Bias and Conflicts of Interest in Analyst Stock Recommendations

Abstract:  This paper tests whether sell-side analysts are prone to behavioural errors when making stock recommendations as well as the impact of investment banking relationships on their judgments. In particular, we analyse their report narratives for evidence of cognitive bias. We find first that new buy recommendations on average have no investment value whereas new sell recommendations do, and take time to be assimilated by the market. We also show that new buy recommendations are distinguished from new sells both by the level of analyst optimism and representativeness bias as well as with increased conflicts of interest. Successful new buy recommendations are characterised by lower prior returns, value stock status, smaller firms and weaker investment banking relationships. On the other hand, successful new sells do not differ from their unsuccessful counterparts in terms of these measures. As such, we provide evidence that analysts are prone both to behavioural bias as well as potential conflicts of interest in their new buy stock recommendation decisions. We also show that these two explanations of analyst behaviour are to a great extent independent of each other. Consequently, the recent attempts by regulators to address potential conflicts of interest in analyst behaviour may have only limited impact.